{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "## load pacakges\n",
    "push!(LOAD_PATH, pwd()) # add the current folder, which contains Utils.jl, to LOAD_PATH\n",
    "using Utils, DataFrames, PyPlot, NLsolve"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "## matplotlib settings\n",
    "#  not important, only to write latex on graphs\n",
    "fontsize = 16; fonttype = \"serif\"\n",
    "# fonttype = \"sansserif\"\n",
    "PyPlot.matplotlib.rc(\"text\", usetex=true) # allow tex rendering\n",
    "PyPlot.matplotlib.rcParams[\"text.latex.unicode\"] = true\n",
    "if fonttype==\"serif\" # use serif math font\n",
    "    PyPlot.matplotlib.rc(\"font\", family=\"serif\", serif=\"Times\", size=16)\n",
    "    #PyPlot.matplotlib.rc(\"text.latex\",preamble=\"\\\\usepackage[libertine]{newtxmath}\")\n",
    "else # use sans serif math font\n",
    "    PyPlot.matplotlib.rc(\"font\", family=\"sans-serif\", size=16)\n",
    "    PyPlot.matplotlib.rc(\"text.latex\",preamble=\"\\\\usepackage{newtxsf}\")\n",
    "end\n",
    "PyPlot.matplotlib.rcParams[\"text.latex.unicode\"] = false;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Functions to solve equilibrium"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "solveDemographics (generic function with 1 method)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## solve for μ given mm and ss for a market\n",
    "function solveDemographics(para)\n",
    "    ρ, n, λu, λd, yh, yd, yl, r, f, qLO, qHN, md, s = para\n",
    "    η = λu/(λu + λd)\n",
    "    function resolveDemographicsX(x)\n",
    "        di = Dict()\n",
    "        di[:mDO] = transBetween(x[1],lower=0.0,upper=md)\n",
    "        di[:mDN] = md - di[:mDO]\n",
    "        di[:νLO] = 1.0 - (1.0 - di[:mDN]/md)^n\n",
    "        di[:νHN] = 1.0 - (1.0 - di[:mDO]/md)^n\n",
    "        di[:mHO] = η*di[:νHN]*(λu + di[:νLO]*ρ)/(λu*di[:νHN] + λd*di[:νLO] + di[:νLO]*di[:νHN]*ρ)\n",
    "        di[:mHN] = η - di[:mHO]\n",
    "        di[:mLO] = (1.0 - η)*(λu*di[:νHN])/(λu*di[:νHN] + λd*di[:νLO] + di[:νLO]*di[:νHN]*ρ)\n",
    "        di[:mLN] = (1.0 - η) - di[:mLO]\n",
    "        return di\n",
    "    end\n",
    "    function f!(fvec,x)\n",
    "        di = resolveDemographicsX(x)\n",
    "        fvec[1] = di[:mHO] + di[:mLO] + di[:mDO] - s\n",
    "    end\n",
    "    sol = nlsolve(f!,rand(1))#,method=:newton)\n",
    "    converging = sol.x_converged | sol.f_converged\n",
    "    return converging, resolveDemographicsX(sol.zero)\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "solveValueFunctions (generic function with 1 method)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## solve for value functions given demographics for a market\n",
    "function solveValueFunctions(para,di0)\n",
    "    ## parameters\n",
    "    ρ, n, λu, λd, yh, yd, yl, r0, f, qLO, qHN, md, s = para\n",
    "    r = r0 + f # combine discount rate with death rate\n",
    "    di = deepcopy(di0)\n",
    "    ## compute the trading gain intensities\n",
    "    di[:ABar] = n*di[:mDO]/md*(1.0 - di[:mDO]/md)^(n-1)/(1.0 - (1.0 - di[:mDO]/md)^n)\n",
    "    di[:BBar] = n*di[:mDN]/md*(1.0 - di[:mDN]/md)^(n-1)/(1.0 - (1.0 - di[:mDN]/md)^n)\n",
    "    di[:ζLO] = di[:mLO]*ρ*di[:νLO]/di[:mLO]*(qLO + (1.0 - qLO)*(1.0 - di[:BBar]))\n",
    "    di[:ζHN] = di[:mHN]*ρ*di[:νHN]/di[:mHN]*(qHN + (1.0 - qHN)*(1.0 - di[:ABar]))\n",
    "    di[:ζDO] = di[:mHN]*ρ*di[:νHN]/di[:mDO]*(1.0 - qHN)*di[:ABar]\n",
    "    di[:ζDN] = di[:mLO]*ρ*di[:νLO]/di[:mDN]*(1.0 - qLO)*di[:BBar]\n",
    "    ## compute value functions, trading gains, and reservation values\n",
    "    ΔDenominator = r^2 + di[:ζDO]*di[:ζLO] + di[:ζLO]*(di[:ζHN] + λd) + di[:ζHN]*λu + di[:ζDO]*(λd + λu) + di[:ζDN]*(di[:ζHN] + λd + λu) + r*(di[:ζDN] + di[:ζDO] + di[:ζHN] + di[:ζLO] + λd + λu)\n",
    "    vDenominator = r*(r + λd + λu)\n",
    "    di[:ΔHD] = maximum([0.0, (yl*(λd - di[:ζDN]) - yd*(r + λd + λu + di[:ζLO]) + yh*(r + λu + di[:ζDN] + di[:ζLO]))/ΔDenominator])\n",
    "    di[:ΔDL] = maximum([0.0, (-yl*(r + λd + di[:ζDO] + di[:ζHN]) + yd*(r + λd + λu + di[:ζHN]) + yh*(di[:ζDO] - λu))/ΔDenominator])\n",
    "    di[:Rd]  = (yd + di[:ζDO]*di[:ΔHD] - di[:ζDN]*di[:ΔDL])/r\n",
    "    di[:Rl]  = ((r + λd)*yl + λu*yh + (r + λd)*di[:ζLO]*di[:ΔDL] - λu*di[:ζHN]*di[:ΔHD])/vDenominator\n",
    "    di[:Rh]  = (λd*yl + (r + λu)*yh + λd*di[:ζLO]*di[:ΔDL] - (r + λu)*di[:ζHN]*di[:ΔHD])/vDenominator\n",
    "    di[:vHO] = ((yl + di[:ΔDL]*di[:ζLO])*λd + yh*(r + λu))/vDenominator\n",
    "    di[:vLN] = di[:ΔHD]*di[:ζHN]*λu/vDenominator\n",
    "    di[:vHN] = di[:ΔHD]*di[:ζHN]*(r + λu)/vDenominator\n",
    "    di[:vLO] = ((yl + di[:ΔDL]*di[:ζLO])*(r + λd) + yh*λu)/vDenominator\n",
    "    di[:vDO] = (yd + di[:ΔHD]*di[:ζDO])/r\n",
    "    di[:vDN] = di[:ΔDL]*di[:ζDN]/r\n",
    "    ## welfare\n",
    "    di[:welfare] = (yh*di[:mHO] + yd*di[:mDO] + yl*di[:mLO])/r0 # use the actual discount rate\n",
    "    ## check if there is positive trading gain\n",
    "    di[:inbound] = (di[:Rh] >= di[:Rd]) & (di[:Rl] <= di[:Rd])\n",
    "    ## return\n",
    "    return di\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Computing equilibrium"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "### calculate equilibrium\n",
    "\n",
    "## default parameters\n",
    "#          ρ,  n,     λu,     λd,  yh,   yd,  yl,    r,   f, qLO, qHN,  md,      s\n",
    "para0 = [1e2, 27, 0.0399, 0.3105, 1.0, 0.90, 0.0, 0.05, 1e2, 0.0, 0.0, 0.1, 0.1205] # based on calibrated values\n",
    "ρ0, n0, λu, λd, yh, yd, yl, r, qLO, qHN, md, s = para0\n",
    "\n",
    "## varying n and rho\n",
    "nRange = 1:100\n",
    "rhoRange = exp.(range(log(1e-1),stop=log(1e2),length=200))\n",
    "\n",
    "## variables of interest\n",
    "liVrb = [:mHN, :mLO, :νHN, :νLO, :welfare, :inbound]\n",
    "\n",
    "## initialize storage\n",
    "diOut = Dict()\n",
    "for pr in liVrb\n",
    "    diOut[pr] = Array{Float64}(undef, length(rhoRange), length(nRange))\n",
    "end\n",
    "\n",
    "## compute\n",
    "for (rr,ρ) in enumerate(rhoRange)\n",
    "    for (cc,n) in enumerate(nRange)\n",
    "        para = copy(para0)\n",
    "        para[1] = ρ; para[2] = n\n",
    "        cvg0, di0 = solveDemographics(para)\n",
    "        di = solveValueFunctions(para,di0)\n",
    "#         di = eqmPrices(para,solveValueFunctions(para,di0))\n",
    "        for pr in liVrb\n",
    "            if cvg0\n",
    "                diOut[pr][rr,cc] = di[pr]\n",
    "            else\n",
    "                diOut[pr][rr,cc] = NaN\n",
    "            end\n",
    "        end\n",
    "    end\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Figure 1: Customer sizes and matching rates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "Figure(PyObject <Figure size 500x500 with 1 Axes>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### Figure 1(a): m_{hn}\n",
    "\n",
    "## specify parameters for plotting\n",
    "prSymbol = :mHN\n",
    "liLevels = [0.001,0.003,0.01,0.03,0.07,]#0.15,0.22]\n",
    "\n",
    "## set up canvas\n",
    "fig = PyPlot.figure(figsize=(5,5), facecolor=\"w\", dpi=100) # create figure\n",
    "fig.subplots_adjust(left=.17, right=.97, bottom=0.15, top=.95) # reduce white spaces\n",
    "ax = fig.add_subplot(111) # create axis\n",
    "ax.set_xscale(\"log\")\n",
    "ax.set_yscale(\"log\")\n",
    "ax.set_xlabel(L\"Search capacity, $n$\")\n",
    "ax.set_ylabel(L\"Search intensity, $\\rho$\")\n",
    "\n",
    "## plot\n",
    "aPlot = copy(diOut[prSymbol])\n",
    "aPlot[diOut[:inbound] .== 0] .= NaN\n",
    "cs = ax.contour(nRange, rhoRange, aPlot, colors=\"b\", levels=liLevels)\n",
    "ax.clabel(cs, inline=1, fontsize=13, fmt=\"%3.3f\",\n",
    "    manual=[(4,0.3),(6,1),(10,5),(15,15),(20,50),]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "Figure(PyObject <Figure size 500x500 with 1 Axes>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### Figure 1(b): m_{lo}\n",
    "\n",
    "## specify parameters for plotting\n",
    "prSymbol = :mLO\n",
    "liLevels = [0.001,0.002,0.005,0.01,0.02,0.04,0.06]\n",
    "\n",
    "## set up canvas\n",
    "fig = PyPlot.figure(figsize=(5,5), facecolor=\"w\", dpi=100) # create figure\n",
    "fig.subplots_adjust(left=.17, right=.97, bottom=0.15, top=.95) # reduce white spaces\n",
    "ax = fig.add_subplot(111) # create axis\n",
    "ax.set_xscale(\"log\")\n",
    "ax.set_yscale(\"log\")\n",
    "ax.set_xlabel(L\"Search capacity, $n$\")\n",
    "ax.set_ylabel(L\"Search intensity, $\\rho$\")\n",
    "\n",
    "## plot\n",
    "aPlot = copy(diOut[prSymbol])\n",
    "aPlot[diOut[:inbound] .== 0] .= NaN\n",
    "cs = ax.contour(nRange, rhoRange, aPlot, colors=\"b\", levels=liLevels)\n",
    "ax.clabel(cs, inline=1, fontsize=13, fmt=\"%3.3f\",\n",
    "    manual=[(30,0.1),(20,0.5),(15,1.2),(10,4),(15,10),(24,20),(40,100)]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "Figure(PyObject <Figure size 500x500 with 1 Axes>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### Figure 1(c): \\nu_{hn}\n",
    "\n",
    "## specify parameters for plotting\n",
    "prSymbol = :νHN\n",
    "liLevels = [0.13; 0.2; 0.4; 0.6; 0.8; 0.9; 0.95; 0.98]\n",
    "\n",
    "## set up canvas\n",
    "fig = PyPlot.figure(figsize=(5,5), facecolor=\"w\", dpi=100) # create figure\n",
    "fig.subplots_adjust(left=.17, right=.97, bottom=0.15, top=.95) # reduce white spaces\n",
    "ax = fig.add_subplot(111) # create axis\n",
    "ax.set_xscale(\"log\")\n",
    "ax.set_yscale(\"log\")\n",
    "ax.set_xlabel(L\"Search capacity, $n$\")\n",
    "ax.set_ylabel(L\"Search intensity, $\\rho$\")\n",
    "\n",
    "## plot\n",
    "aPlot = copy(diOut[prSymbol]); aPlot[diOut[:inbound] .== 0] .= NaN\n",
    "cs = ax.contour(nRange, rhoRange, aPlot, colors=\"b\", levels=liLevels)\n",
    "ax.clabel(cs, inline=1, fontsize=13, fmt=\"%3.2f\",\n",
    "    manual=[(1.3,60),(2.0,30),(3.5,5),(7,2),(15,1),(20,0.5),(30,0.3),(90,0.2)]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "Figure(PyObject <Figure size 500x500 with 1 Axes>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### Figure 1(d): \\nu_{lo}\n",
    "\n",
    "## specify parameters for plotting\n",
    "prSymbol = :νLO\n",
    "liLevels = [0.7,0.8,0.9,0.95,0.99,0.999,0.99999,1-1e-8,1-1e-12]\n",
    "liLevelStr = [\"0.7\",\"0.8\",\"0.9\",\"0.95\",\"0.99\",\"0.999\",L\"$1-10^{-5}$\",L\"$1-10^{-8}$\",L\"$1-10^{-12}$\"]\n",
    "\n",
    "## set up canvas\n",
    "fig = PyPlot.figure(figsize=(5,5), facecolor=\"w\", dpi=100) # create figure\n",
    "fig.subplots_adjust(left=.17, right=.97, bottom=0.15, top=.95) # reduce white spaces\n",
    "ax = fig.add_subplot(111) # create axis\n",
    "ax.set_xscale(\"log\")\n",
    "ax.set_yscale(\"log\")\n",
    "ax.set_xlabel(L\"Search capacity, $n$\")\n",
    "ax.set_ylabel(L\"Search intensity, $\\rho$\")\n",
    "\n",
    "## plot\n",
    "aPlot = copy(diOut[prSymbol]); aPlot[diOut[:inbound] .== 0] .= NaN\n",
    "cs = ax.contour(nRange, rhoRange, aPlot, colors=\"b\", levels=liLevels)\n",
    "fmt = Dict(); for (l,s) in zip(cs.levels, liLevelStr)\n",
    "    fmt[l] = s\n",
    "end\n",
    "ax.clabel(cs, inline=1, fontsize=13, fmt=fmt,\n",
    "    manual=[(1,7e-1),(1.3,2),(1.5,10),(2.5,0.3),(3.0,2),(5.0,1),(6.0,10),(8.0,20),(15.0,2)]);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Figure 2: Search technology and welfare"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "Figure(PyObject <Figure size 500x500 with 1 Axes>)"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "## specify parameters for plotting\n",
    "prSymbol = :welfare\n",
    "liLevels = [0.6,1.0,1.5,2.0,2.2,2.3,2.35]\n",
    "\n",
    "## set up canvas\n",
    "fig = PyPlot.figure(figsize=(5,5), facecolor=\"w\", dpi=100) # create figure\n",
    "fig.subplots_adjust(left=.17, right=.97, bottom=0.15, top=.95) # reduce white spaces\n",
    "ax = fig.add_subplot(111) # create axis\n",
    "ax.set_xscale(\"log\")\n",
    "ax.set_yscale(\"log\")\n",
    "ax.set_xlabel(L\"Search capacity, $n$\")\n",
    "ax.set_ylabel(L\"Search intensity, $\\rho$\")\n",
    "\n",
    "## plot\n",
    "aPlot = copy(diOut[prSymbol])\n",
    "aPlot[diOut[:inbound] .== 0] .= NaN\n",
    "cs = ax.contour(nRange, rhoRange, aPlot, colors=\"b\", levels=liLevels)\n",
    "ax.clabel(cs, inline=1, fontsize=13, fmt=\"%3.2f\",\n",
    "    manual=[(30,1e-1),(25,3e-1),(20,2),(15,3),(12,8),(10,20)]);"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Julia 1.6.5",
   "language": "julia",
   "name": "julia-1.6"
  },
  "language_info": {
   "file_extension": ".jl",
   "mimetype": "application/julia",
   "name": "julia",
   "version": "1.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
